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    DEVELOPMENT OF A CITY-WIDE TREE INVENTORY FOR THE CITY OF SEATTLE WASHINGTON

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    MS-GIST_2023_Williams.pdf
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    Description:
    MS-GIST Report
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    Author
    Williams, Connor
    Issue Date
    2023-08
    Keywords
    Trees
    Urban Forestry
    Model Builder
    Python
    City Government
    GIS
    Advisor
    Mason, Jennifer
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Collection Information
    This item is part of the MS-GIST Master's Reports collection. For more information about items in this collection, please contact the UA Campus Repository at repository@u.library.arizona.edu.
    Abstract
    Seattle is the largest city in Washington State and has an estimated tree canopy cover of 28.1%. The health of the urban forest is a critical part of what gives the city its identity, as well as providing important ecosystem services to the city’s residents. The city is slowly losing its canopy through time, and the neighborhoods where canopy loss is happening the fastest have histories of economic and racial inequality. Various departments across the municipality are responsible for managing trees and they need to work together to manage the urban forest. Unfortunately, these departments each track only the trees they are directly responsible for. In this study I describe the methods used to design and create a combined tree inventory of all trees tracked and managed by the city of Seattle. I then use the resulting combined tree inventory to perform several example analyses that an urban forester at the city might perform. I found that this was a reliable method to manage the complex integration of many contributing data sources into a single, simple, user-friendly dataset while also supporting the inevitable changes made to the contributing datasets as business needs evolve.
    Type
    Electronic Report
    text
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Geographic Information Systems Technology
    Degree Grantor
    University of Arizona
    Collections
    MS-GIST (Master's Reports)

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